Crisp dm
7 important questions on Crisp dm
Which phases are there in the crisp dm model?
- Business understanding
- Data understanding
- data preparation
- modeling
- evaluation
- deployment
What are the characteristics of the business understanding phase?
- This is the phase where you want to understand the question the client has for you
- to do this you want to have an understanding of what their company is like: company culture, mission, strategy
- You want to become aware of stakeholders: who has interest in this project, and who do i need to keep happy the most?
- you want to translate your business problem to a data science problem
- the goals of this phase are accomplished by having a client interview
What are the characteristics of the data understanding phase
- In this phase you want to explore what data is available to you and how it can be used to answer the question of the client
- steps in this phase can be:
- data acquiring
- data exploring
- verifying data quality
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What are characteristics of the data preparation phase?
- In the data preparation phase you'll reshape your data to make it fit for modelling
- steps in this phase can be:
- Joining datasets
- selecting variables
- data cleaning
- feature extraction
- formatting data
What are some characteristics of the modeling phase?
- In the modeling phase you built and evaluate different models to answer your question
- ensure that you employ models that the client is comfortable with: start out simple and only use more complex models if you have to.
- client satisfaction is most important so with every increase in model complexity the client satisfaction may decrease
What are characteristics of the evaluation phase?
- In the evaluation phase you review whether the results from the modeling phase satisfy the client
- determine whether they understand what you did an are happy with the modeling result
What are characteristics of the deployment phase?
- In this phase your data analysis gets translated back to the business level
- the entire process is described and modeling results are transformed to an agreed upon finish product like an advise or a dashboard.
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